class_docstr: Display mismatch between raw types between datasets provided. In case if mismatch found, mark the row with a warning.
  
  The report requires :py:class:`~autogluon.eda.analysis.dataset.RawTypesAnalysis` analysis present.
  
  Parameters
  ----------
  headers: bool, default = False
      if `True` then render headers
  namespace: str, default = None
      namespace to use; can be nested like `ns_a.ns_b.ns_c`
  
  Examples
  --------
  >>> import autogluon.eda.analysis as eda
  >>> import autogluon.eda.visualization as viz
  >>> import autogluon.eda.auto as auto
  >>> auto.analyze(
  >>>     train_data=..., test_data=...,
  >>>     anlz_facets=[
  >>>         eda.dataset.RawTypesAnalysis(),
  >>>     ],
  >>>     viz_facets=[
  >>>         viz.dataset.DatasetTypeMismatch()
  >>>     ]
  >>> )
  
  See Also
  --------
  :py:class:`~autogluon.eda.analysis.dataset.RawTypesAnalysis`
code: def __init__(
      self,
      headers: bool = False,
      namespace: Optional[str] = None,
      **kwargs,
  ) -> None:
      super().__init__(namespace, **kwargs)
      self.headers = headers
  
imports: from typing import Any, Dict, List, Optional
  import pandas
  from pandas import DataFrame
  from ..state import AnalysisState
  from .base import AbstractVisualization
  from .jupyter import JupyterMixin
label_desc: Use image node_id 1 to create a new DatasetTypeMismatch object from inherited base classes: AbstractVisualization, JupyterMixin with example: obj = DatasetTypeMismatch(headers, namespace)